Full-Stack AI Engineer

ChipAgents•San Jose, CA

14h•Onsite

About The Position

ChipAgents is redefining the future of chip design and verification with agentic AI workflows. Our platform leverages cutting-edge generative AI to assist engineers in RTL design, simulation, and verification, dramatically accelerating chip development. Founded by experts in AI and semiconductor engineering, we partner with top semiconductor firms, cloud providers, and innovative startups to build intelligent AI agents. The company is a Series A company backed by tier-1 VC firms. ChipAgents is deployed in production to companies that have shipped 16B chips.

Requirements

B.S. or M.S. in Computer Science or a related field.
Experience building full-stack software, with strong fundamentals in software engineering and machine learning.
Familiarity with modern ML workflows (e.g., Python, PyTorch, LLMs, etc.) and frontend development tools (e.g., TypeScript, JavaScript).
Interest in electronic design automation (EDA), RTL, or hardware-software co-design (prior exposure is a plus, but not required).
Excellent communication skills and comfort working directly with customer engineering teams.
Willingness to travel for on-site customer visits and deep integration work.
A self-starter who thrives in a fast-paced, mission-driven startup environment.

Nice To Haves

prior exposure to electronic design automation (EDA), RTL, or hardware-software co-design is a plus

Responsibilities

Own the technical success of ChipAgents deployments from start to finish: onboarding, integration, scaling, and feedback.
Interface directly with customer engineering teams to understand their workflows and identify high-leverage opportunities for AI automation.
Prototype and refine full-stack solutions—from backend models to frontend experiences—that embed agentic AI into EDA workflows.
Collaborate with our core engineering team to improve models, tooling, and infrastructure based on field insights.
Create internal and customer-facing resources (docs, tutorials, dashboards) that scale our support and enable rapid adoption.
Stay hands-on with code: contribute to infrastructure, prompt engineering, workflow orchestration, and feedback-driven improvement.